
\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/develop_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it develop}.}
  \label{develop:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/develop_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it develop}.}
  \label{develop:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/develop_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it develop}.}
  \label{develop:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Psychiatry & NP & 0.399905 & NP-PRED-RS & 0.141902 & NP-FOR-NP & 0.137602 \\
Education & NP & 0.328025 & NP-FOR-NP & 0.140127 & INTRANS & 0.121019 \\
Environmental Health & NP & 0.309671 & INTRANS & 0.138097 & NP-FOR-NP & 0.128797 \\
Pharmacology & NP & 0.441249 & NP-FOR-NP & 0.118324 & NP-PRED-RS & 0.115859 \\
Geriatrics & NP & 0.390192 & NP-PRED-RS & 0.140725 & NP-FOR-NP & 0.115139 \\
Public Health & NP & 0.361242 & NP-FOR-NP & 0.158063 & NP-PP-PRED & 0.101749 \\
Biotechnology & NP & 0.356888 & NP-FOR-NP & 0.173096 & NP-PRED-RS & 0.098217 \\
Biomedical Engineering & NP & 0.385159 & NP-FOR-NP & 0.169611 & NP-PP-PRED & 0.111307 \\
Medical Informatics & NP & 0.410649 & NP-FOR-NP & 0.168911 & NP-PP-PRED & 0.083231 \\
Obstetrics & NP & 0.315455 & INTRANS & 0.152435 & NP-PRED-RS & 0.120678 \\
Medicine & NP & 0.345473 & NP-PRED-RS & 0.137849 & NP-PP-PRED & 0.091899 \\
Genetics, Medical & NP & 0.303856 & NP-PRED-RS & 0.143445 & NP-FOR-NP & 0.114139 \\
Tropical Medicine & NP & 0.345211 & INTRANS & 0.116705 & NP-PRED-RS & 0.114743 \\
Microbiology & NP & 0.293089 & NP-FOR-NP & 0.127123 & NP-PRED-RS & 0.095342 \\
Neoplasms & NP & 0.304064 & NP-PRED-RS & 0.147233 & NP-PP-PRED & 0.099857 \\
Critical Care & NP & 0.340197 & NP-PRED-RS & 0.182325 & INTRANS & 0.099528 \\
Molecular Biology & NP & 0.245846 & NP-FOR-NP & 0.156345 & NP-PP-PRED & 0.100831 \\
Physiology & NP & 0.366467 & NP-FOR-NP & 0.131138 & NP-PRED-RS & 0.100599 \\
Veterinary Medicine & NP & 0.287117 & NP-PRED-RS & 0.117791 & INTRANS & 0.099387 \\
Science & NP & 0.263721 & INTRANS & 0.128445 & NP-PP-PRED & 0.109314 \\
Genetics & NP & 0.261829 & NP-FOR-NP & 0.142401 & INTRANS & 0.107713 \\
Neurology & NP & 0.231093 & INTRANS & 0.207683 & NP-PP-PRED & 0.103842 \\
Cell Biology & NP & 0.223591 & INTRANS & 0.200704 & PP-PRED-RS & 0.084507 \\
Therapeutics & NP & 0.350314 & NP-FOR-NP & 0.155172 & NP-PRED-RS & 0.101097 \\
Endocrinology & NP & 0.273525 & INTRANS & 0.161085 & NP-PRED-RS & 0.137959 \\
Communicable Diseases & NP & 0.287262 & NP-PRED-RS & 0.149480 & INTRANS & 0.144714 \\
Pediatrics & NP & 0.361596 & NP-PRED-RS & 0.194514 & INTRANS & 0.124688 \\
Biochemistry & NP & 0.285505 & INTRANS & 0.231332 & NP-FOR-NP & 0.120059 \\
Botany & NP & 0.281346 & INTRANS & 0.189602 & NP-FOR-NP & 0.128440 \\
Virology & NP & 0.379412 & NP-PRED-RS & 0.136275 & NP-FOR-NP & 0.109804 \\
Gastroenterology & NP & 0.334848 & NP-PRED-RS & 0.210606 & NP-PP-PRED & 0.127273 \\
Pulmonary Medicine & NP & 0.300429 & NP-PRED-RS & 0.158798 & NP-PP-PRED & 0.115880 \\
Ethics & NP & 0.274298 & INTRANS & 0.228942 & NP-PP-PRED & 0.155508 \\
Vascular Diseases & NP & 0.318367 & NP-PRED-RS & 0.155102 & INTRANS & 0.101224 \\
Rheumatology & NP & 0.306562 & NP-PRED-RS & 0.159647 & NP-PP-PRED & 0.119491 \\
Ophthalmology & NP & 0.245421 & NP-PRED-RS & 0.146520 & INTRANS & 0.124542 \\
Embryology & INTRANS & 0.510504 & INTRANS-RECIPSUBJ-PL & 0.172269 & NP & 0.120798 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it develop}.}
\label{develop:table}
\end{figure*}
\clearpage

\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/express_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it express}.}
  \label{express:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/express_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it express}.}
  \label{express:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/express_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it express}.}
  \label{express:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Genetics & NP & 0.484719 & NP-PP-PRED & 0.088202 & NP-PRED-RS & 0.077303 \\
Cell Biology & NP & 0.436123 & NP-PRED-RS & 0.256388 & NP-PP-PRED & 0.183260 \\
Genetics, Medical & NP & 0.445434 & NP-PRED-RS & 0.084633 & NP-PP-PRED & 0.082405 \\
Biochemistry & NP & 0.320611 & NP-PRED-RS & 0.122137 & NP-AS-NP-SC & 0.113700 \\
Botany & NP & 0.457393 & NP-PRED-RS & 0.107769 & PP-PRED-RS & 0.084586 \\
Molecular Biology & NP & 0.401806 & NP-PP-PRED & 0.151806 & NP-PRED-RS & 0.125282 \\
Microbiology & NP & 0.393716 & NP-PRED-RS & 0.192811 & NP-PP-PRED & 0.152821 \\
Tropical Medicine & NP & 0.362590 & NP-AS-NP-SC & 0.152518 & NP-AS-NP & 0.152518 \\
Pharmacology & NP & 0.300459 & NP-AS-NP-SC & 0.181193 & NP-AS-NP & 0.181193 \\
Physiology & NP & 0.320866 & NP-AS-NP-SC & 0.140748 & NP-AS-NP & 0.140748 \\
Endocrinology & NP & 0.389426 & NP-PRED-RS & 0.131325 & NP-AS-NP-SC & 0.117112 \\
Neoplasms & NP & 0.439103 & NP-PP-PRED & 0.200038 & NP-PRED-RS & 0.171003 \\
Biotechnology & NP & 0.416469 & NP-PRED-RS & 0.182106 & NP-PP-PRED & 0.165479 \\
Rheumatology & NP & 0.435431 & NP-PRED-RS & 0.136413 & NP-PP-PRED & 0.132412 \\
Neurology & NP & 0.384721 & NP-PP-PRED & 0.137646 & NP-PRED-RS & 0.135582 \\
Communicable Diseases & NP & 0.336735 & NP-AS-NP-SC & 0.204082 & NP-AS-NP & 0.204082 \\
Virology & NP & 0.388041 & NP-PRED-RS & 0.227216 & NP-PP-PRED & 0.185567 \\
Science & NP & 0.392503 & NP-PRED-RS & 0.172770 & NP-PP-PRED & 0.138302 \\
Medicine & NP & 0.396785 & NP-PRED-RS & 0.167203 & NP-PP-PRED & 0.154984 \\
Vascular Diseases & NP-AS-NP-SC & 0.281022 & NP-AS-NP & 0.281022 & NP & 0.253650 \\
Pulmonary Medicine & NP & 0.328225 & NP-AS-NP-SC & 0.186462 & NP-AS-NP & 0.186462 \\
Environmental Health & NP & 0.281679 & NP-AS-NP-SC & 0.167877 & NP-AS-NP & 0.167877 \\
Public Health & NP & 0.266667 & NP-PP-PRED & 0.183333 & NP-PP & 0.126190 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it express}.}
\label{express:table}
\end{figure*}
\clearpage

\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/perform_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it perform}.}
  \label{perform:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/perform_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it perform}.}
  \label{perform:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/perform_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it perform}.}
  \label{perform:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Medical Informatics & NP & 0.361941 & NP-PP-PRED & 0.177756 & NP-PRED-RS & 0.084217 \\
Education & NP & 0.442718 & NP-PRED-RS & 0.116505 & INTRANS & 0.100971 \\
Molecular Biology & NP & 0.248283 & NP-ING-SC & 0.124142 & NP-ING-OC & 0.124142 \\
Genetics, Medical & NP & 0.262342 & NP-ING-SC & 0.120675 & NP-ING-OC & 0.120675 \\
Pharmacology & NP & 0.304765 & NP-PP-PP PFORM & 0.146923 & NP-ING-SC & 0.102581 \\
Critical Care & NP & 0.441001 & NP-PP-PP PFORM & 0.080182 & NP-ING-SC & 0.075064 \\
Communicable Diseases & NP & 0.431208 & NP-ING-SC & 0.075201 & NP-ING-OC & 0.075201 \\
Gastroenterology & NP & 0.484485 & NP-PP-PP PFORM & 0.070187 & NP-ING-SC & 0.069537 \\
Therapeutics & NP & 0.511537 & NP-FOR-NP & 0.065702 & NP-ING-SC & 0.057880 \\
Ophthalmology & NP & 0.536599 & NP-PP-PRED & 0.057788 & NP-ING-SC & 0.055036 \\
Obstetrics & NP & 0.454327 & NP-PP-PRED & 0.079327 & NP-ING-SC & 0.066106 \\
Biomedical Engineering & NP & 0.393035 & NP-PP-PRED & 0.074627 & NP-TO-INF-OC & 0.073383 \\
Pulmonary Medicine & NP & 0.374464 & NP-PP-PP PFORM & 0.094271 & NP-ING-SC & 0.092366 \\
Medicine & NP & 0.362900 & NP-ING-SC & 0.099518 & NP-ING-OC & 0.099518 \\
Physiology & NP & 0.394495 & NP-ING-SC & 0.083524 & NP-ING-OC & 0.083524 \\
Neoplasms & NP & 0.382559 & NP-PP-PP PFORM & 0.091148 & NP-ING-SC & 0.083187 \\
Rheumatology & NP & 0.333756 & NP-PP-PP PFORM & 0.106480 & NP-ING-SC & 0.089181 \\
Neurology & NP & 0.331288 & NP-PP-PP PFORM & 0.105171 & NP-ING-SC & 0.088721 \\
Tropical Medicine & NP & 0.370042 & NP-ING-SC & 0.105513 & NP-ING-OC & 0.105513 \\
Psychiatry & NP & 0.381216 & NP-PRED-RS & 0.092344 & NP-PP-PRED & 0.092344 \\
Environmental Health & NP & 0.300141 & NP-PP-PRED & 0.103796 & NP-ING-SC & 0.091065 \\
Pediatrics & NP & 0.450953 & NP-PRED-RS & 0.073572 & NP-PP-PRED & 0.062320 \\
Veterinary Medicine & NP & 0.407389 & NP-ING-SC & 0.099351 & NP-ING-OC & 0.099351 \\
Vascular Diseases & NP & 0.444747 & NP-ING-SC & 0.089117 & NP-ING-OC & 0.089117 \\
Geriatrics & NP & 0.457423 & NP-PRED-RS & 0.080250 & NP-TO-INF-VC & 0.072671 \\
Virology & NP & 0.312346 & NP-ING-SC & 0.115070 & NP-ING-OC & 0.115070 \\
Embryology & NP & 0.260802 & NP-ING-SC & 0.135802 & NP-ING-OC & 0.135802 \\
Microbiology & NP & 0.276414 & NP-ING-SC & 0.126016 & NP-ING-OC & 0.126016 \\
Botany & NP & 0.249518 & NP-ING-SC & 0.131218 & NP-ING-OC & 0.131218 \\
Biochemistry & NP & 0.264828 & NP-ING-SC & 0.134100 & NP-ING-OC & 0.134100 \\
Science & NP & 0.255107 & NP-ING & 0.130580 & NP-ING-OC & 0.130580 \\
Genetics & NP & 0.305055 & NP-ING & 0.114337 & NP-ING-OC & 0.114337 \\
Biotechnology & NP & 0.337702 & NP-ING & 0.107471 & NP-ING-OC & 0.107471 \\
Cell Biology & NP & 0.297386 & NP-ING & 0.153232 & NP-ING-OC & 0.153232 \\
Public Health & NP & 0.338684 & NP-PRED-RS & 0.097372 & NP-TO-INF-VC & 0.081143 \\
Endocrinology & NP & 0.352185 & NP-ING & 0.141674 & NP-ING-OC & 0.141674 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it perform}.}
\label{perform:table}
\end{figure*}
\clearpage

\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/predict_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it predict}.}
  \label{predict:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/predict_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it predict}.}
  \label{predict:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/predict_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it predict}.}
  \label{predict:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Vascular Diseases & NP-PP-PRED & 0.319039 & NP & 0.259005 & NP-PRED-RS & 0.197256 \\
Psychiatry & NP & 0.296053 & NP-PP-PRED & 0.265351 & NP-PRED-RS & 0.155702 \\
Public Health & NP & 0.313056 & NP-PP-PRED & 0.258160 & NP-PRED-RS & 0.143917 \\
Medicine & NP & 0.333758 & NP-PP-PRED & 0.249682 & NP-PRED-RS & 0.152866 \\
Communicable Diseases & NP-PP-PRED & 0.272923 & NP & 0.242837 & NP-PRED-RS & 0.139685 \\
Physiology & NP & 0.297170 & NP-PP-PRED & 0.266509 & NP-PRED-RS & 0.127358 \\
Neoplasms & NP-PP-PRED & 0.301850 & NP & 0.252678 & NP-PP & 0.176241 \\
Critical Care & NP & 0.321659 & NP-PP-PRED & 0.291244 & NP-PRED-RS & 0.185253 \\
Pulmonary Medicine & NP & 0.610138 & NP-PP-PRED & 0.117051 & NP-PRED-RS & 0.073733 \\
Rheumatology & NP & 0.287570 & NP-PP-PRED & 0.257885 & NP-PRED-RS & 0.150278 \\
Environmental Health & NP & 0.356804 & NP-PP-PRED & 0.259309 & NP-PRED-RS & 0.119838 \\
Neurology & NP & 0.239140 & NP-PP-PRED & 0.174610 & HAT-S & 0.115141 \\
Biotechnology & NP & 0.304348 & NP-PP-PRED & 0.214393 & NP-TOBE & 0.143928 \\
Virology & NP & 0.176289 & NP-TOBE & 0.139175 & NP-PP-PRED & 0.126804 \\
Biochemistry & NP-PP-PRED & 0.190345 & NP & 0.167586 & NP-TOBE & 0.124138 \\
Tropical Medicine & NP & 0.261468 & NP-PP-PRED & 0.133486 & NP-PRED-RS & 0.104587 \\
Molecular Biology & NP & 0.212812 & NP-PP-PRED & 0.185082 & NP-TOBE & 0.105761 \\
Microbiology & NP & 0.211287 & NP-TOBE & 0.165237 & NP-TO-INF-OC & 0.125508 \\
Botany & NP & 0.265457 & NP-TOBE & 0.139535 & NP-TO-INF-OC & 0.119682 \\
Genetics & NP & 0.258138 & NP-PP-PRED & 0.137358 & NP-TOBE & 0.103301 \\
Genetics, Medical & NP & 0.277823 & NP-PP-PRED & 0.187652 & NP-TO-INF-OC & 0.130788 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it predict}.}
\label{predict:table}
\end{figure*}
\clearpage

\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/recognize_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it recognize}.}
  \label{recognize:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/recognize_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it recognize}.}
  \label{recognize:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/recognize_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it recognize}.}
  \label{recognize:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Public Health & NP & 0.257610 & NP-PP-PRED & 0.125464 & NP-AS-NP & 0.096511 \\
Environmental Health & NP & 0.302128 & HAT-S & 0.093617 & NP-PP-PRED & 0.093617 \\
Medicine & NP & 0.413386 & NP-PP-PRED & 0.118110 & NP-PRED-RS & 0.100394 \\
Medical Informatics & NP & 0.332331 & NP-PP-PRED & 0.169925 & IT-PASS-SFIN & 0.075188 \\
Tropical Medicine & NP & 0.423986 & NP-S & 0.108108 & IT-PASS-SFIN & 0.104730 \\
Vascular Diseases & NP & 0.251641 & IT-PASS-SFIN & 0.157549 & NP-AS-NP-SC & 0.135667 \\
Pulmonary Medicine & NP & 0.362429 & IT-PASS-SFIN & 0.132827 & NP-S & 0.121442 \\
Neoplasms & NP & 0.447775 & NP-PP-PRED & 0.117166 & NP-AS-NP-SC & 0.101726 \\
Neurology & NP & 0.396584 & NP-PP-PRED & 0.146110 & NP-PRED-RS & 0.104364 \\
Rheumatology & NP & 0.505841 & NP-PP-PRED & 0.156542 & NP-PRED-RS & 0.096963 \\
Genetics & NP & 0.491974 & NP-PP-PRED & 0.130016 & NP-PRED-RS & 0.108347 \\
Microbiology & NP & 0.505447 & NP-PP-PRED & 0.159041 & NP-PRED-RS & 0.100218 \\
Virology & NP & 0.525084 & NP-PP-PRED & 0.158863 & NP-PRED-RS & 0.107023 \\
Science & NP & 0.530660 & NP-PP-PRED & 0.136792 & NP-PRED-RS & 0.106132 \\
Communicable Diseases & NP & 0.463087 & NP-AS-NP-SC & 0.194631 & NP-AS-NP & 0.194631 \\
Biochemistry & NP & 0.465596 & NP-PP-PRED & 0.135321 & NP-PRED-RS & 0.080275 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it recognize}.}
\label{recognize:table}
\end{figure*}
\clearpage

\newpage
\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/treat_heatmap.png}
  \caption{Heat map of Jensen-Shannon divergence between subdomains for the SCF distributions of {\it treat}.}
  \label{treat:hm}
\end{figure*}

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/treat_dendrogram.png}
  \caption{Hierarchical clustering of subdomains via average-linking for the SCF distributions of {\it treat}.}
  \label{treat:dend}
\end{figure*}

\newpage

\begin{figure*}
  \centering
  \includegraphics[height=.4\textheight]{figures/treat_pca.png}
  \caption{Two-dimensional PCA reduction with Gap-statistic-optimal clustering for the SCF distributions of {\it treat}.}
  \label{treat:pca}
\end{figure*}

\begin{figure*}
\centering
\scriptsize
\begin{tabular}{| l | l l | l l | l l |}
    \hline
    Subdomain & \multicolumn{6}{| c |}{Top three SCFs} \\
    \hline
    Pulmonary Medicine & NP & 0.337748 & NP-PP-PP PFORM & 0.167770 & NP-NP-PRED & 0.129139 \\
Pharmacology & NP & 0.274845 & NP-NP-PRED & 0.184783 & NP-NP & 0.184783 \\
Veterinary Medicine & NP & 0.360000 & NP-FOR-NP & 0.120000 & NP-PP-PP PFORM & 0.106667 \\
Vascular Diseases & NP & 0.388060 & PP & 0.099502 & PP-PRED-RS & 0.099502 \\
Tropical Medicine & NP & 0.425547 & NP-NP-PRED & 0.103035 & NP-NP & 0.103035 \\
Medicine & NP & 0.355288 & NP-PP-PP PFORM & 0.126160 & NP-PRED-RS & 0.080705 \\
Communicable Diseases & NP & 0.353806 & NP-PP-PP PFORM & 0.173010 & NP-FOR-NP & 0.121107 \\
Neoplasms & NP & 0.314900 & NP-PP-PP PFORM & 0.219662 & PP-PRED-RS & 0.094470 \\
Biochemistry & NP & 0.252427 & NP-PP-PP PFORM & 0.200647 & PP-PRED-RS & 0.101942 \\
Endocrinology & NP & 0.240283 & NP-PP-PP PFORM & 0.207303 & PP-PP & 0.089517 \\
Rheumatology & NP & 0.283192 & NP-PP-PP PFORM & 0.203390 & PP & 0.133475 \\
Science & NP-PP-PP PFORM & 0.224299 & NP & 0.190314 & PP-PP & 0.115548 \\
Neurology & NP & 0.260030 & NP-PP-PP PFORM & 0.228826 & NP-NP-PRED & 0.123328 \\
Virology & NP-PP-PP PFORM & 0.300000 & NP & 0.209524 & NP-NP-PRED & 0.102381 \\
Microbiology & NP-PP-PP PFORM & 0.322925 & NP & 0.201828 & PP-PRED-RS & 0.105864 \\
Cell Biology & NP-PP-PP PFORM & 0.389027 & NP & 0.182045 & PP-PP & 0.114713 \\
Botany & NP & 0.214421 & NP-PP-PP PFORM & 0.204934 & NP-NP & 0.100569 \\
Physiology & NP & 0.358191 & NP-PP-PP PFORM & 0.107579 & NP-NP-PRED & 0.074572 \\
Environmental Health & NP & 0.385877 & NP-PP-PP PFORM & 0.091298 & NP-AS-NP-SC & 0.077746 \\
Genetics & NP & 0.211664 & NP-PP-PP PFORM & 0.189040 & NP-AS-NP-SC & 0.096531 \\
Molecular Biology & NP-PP-PP PFORM & 0.281690 & NP & 0.170775 & PP-PP & 0.070423 \\
Geriatrics & NP & 0.346975 & NP-PRED-RS & 0.097865 & NP-PP-PRED & 0.088968 \\
Critical Care & NP & 0.413424 & NP-PP-PP PFORM & 0.108949 & PP-PRED-RS & 0.090467 \\
Gastroenterology & NP & 0.546099 & NP-PP-PP PFORM & 0.148936 & PP-PRED-RS & 0.083333 \\
Public Health & NP & 0.342735 & NP-FOR-NP & 0.124786 & NP-AS-NP-SC & 0.101709 \\

\hline
\end{tabular}
\caption{Top three SCFs, by subdomain, for {\it treat}.}
\label{treat:table}
\end{figure*}
\clearpage
